A mathematical model of fiber orientation in slivers

Neckář, Bohuslav; Das, Dipayan; Ishtiaque, S. M.

doi:10.1080/00405000.2011.586153

Cited by 14 publications

(9 citation statements)

References 6 publications

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“…A fi nisher draw frame is an imperative stage among the spinning preparatory processes since the inadequacies present in the combed draft ed sliver will surely pass into the yarn and the defect in a fi nished combed sliver could not be rectifi ed on subsequent machines. According to previous studies, the alignment of fi bres in the sliver confi guration improved the drawing of combed sliver [8][9][10]. Combed sliver with its low inter-fi bre friction is more prone to falsifi ed draft and stretching [11].…”

Section: Izvlečekmentioning

confidence: 99%

Effect of finisher draw frame variables on combed cotton yarn quality

Singh¹,

Bhowmick²,

Vaz³

2018

TEK

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This research work is an outcome of a practical problem experienced at a fi nisher draw frame machine in the spinning preparatory section. Older storage can-spring stiff ness decreases due to fatigue loading over the years. Hence, combed sliver characteristics may vary during the storage, transportation and processing on a subsequent machine. The study aims to investigate the infl uence of the can-spring stiff ness factor, sliver deposition rate and sliver coils position on the combed yarn coeffi cient of variation of mass, imperfections and hairiness. For research design, the three-factor three levels Box-Behnken experimental design was adopted. Moreover, the analysis of variance was performed to check the statistical signifi cance of all observed responses.

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Section: Izvlečekmentioning

confidence: 99%

Effect of finisher draw frame variables on combed cotton yarn quality

Singh¹,

Bhowmick²,

Vaz³

2018

TEK

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“…Under quite general conditions this statistic follows asymptotically the χ 2 distribution with r -1 degrees of freedom. This allows not only deciding about the null hypothesis, but also calculating corresponding p -values.…”

Section: Monitoring Homogeneity Of Orientation Of Fibersmentioning

confidence: 99%

“…Recall that when the p -value is smaller than the predetermined significance level, α , which is in technical practice usually set to 0.05, the test rejects the null hypothesis. For details about χ 2 testing of fitness and its applications in industry see, for example, Nagla, 28 Montgomery, 29 or Greenwood and Nikulin. 30…”

Section: Monitoring Homogeneity Of Orientation Of Fibersmentioning

confidence: 99%

“…An image of the size 2000 × 4000 pixels displays a simulated fibrous system with the random orientation of objects, which in the middle contains specifically oriented fibers with a strong directional orientation α ∈ (0, π /6). We calculated a χ 2 goodness-of-fit test against the uniform distribution for a sliding window (inspection area of the size 1000 × 1000 pixels), which is systematically moved over the whole image area either with or without overlapping. Overlapping was set to the half of the size of the monitoring window.…”

Section: Monitoring Homogeneity Of Orientation Of Fibersmentioning

confidence: 99%

“…Therefore, the determination of directional orientation of any fibrous structure is an important part of quantitative measurements, not only in textile metrology and practice. 1–7…”

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confidence: 99%

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Monitoring homogeneity of textile fiber orientation

Tunák

Antoch

2017

Textile Research Journal

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Replacement of human control by robotic control is one of the key issues in the textile industry, because it is generally believed that it can decrease the costs of producers on the one hand and increase the satisfaction of clients on the other side. Therefore, this paper deals with the proposal of monitoring homogeneity in fibrous systems when the attention is focused on keeping prescribed directional orientation of fibers. The first part concentrates on the estimation of the orientation of fibers in fibrous systems when the information comes from scanned images of the material. Emphasis is on the use of 2D Fourier transform and a local approach based on idea “conquer and rule”. Such a local approach appears crucial for a proposal how to detect eventual defects, random violation of structural regularity, and such like, when statistical testing of fit is used as a tool. To illustrate the method, it was necessary to prepare data with a prescribed form and orientation of fibers. To that purpose we developed algorithms enabling us to simulate images imitating typical textile fibrous systems with prescribed properties, both containing and not containing defects. Linear and highly nonlinear fibers can be generated. The paper is of a methodological nature, and most of conclusions are based on the analysis of simulated data. Experimental verification of the suggested method is in progress.

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Influence of Punching Parameters on Fibre Orientation and Related Physical and Mechanical Properties of Needle Punched Nonwoven

Roy

Ishtiaque

2019

Fibers Polym

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A mathematical model of fiber orientation in slivers

Cited by 14 publications

References 6 publications

Effect of finisher draw frame variables on combed cotton yarn quality

Effect of finisher draw frame variables on combed cotton yarn quality

Monitoring homogeneity of textile fiber orientation

Influence of Punching Parameters on Fibre Orientation and Related Physical and Mechanical Properties of Needle Punched Nonwoven

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